Cosmin Safta

1.4k total citations
75 papers, 829 citations indexed

About

Cosmin Safta is a scholar working on Statistics, Probability and Uncertainty, Computational Mechanics and Artificial Intelligence. According to data from OpenAlex, Cosmin Safta has authored 75 papers receiving a total of 829 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Statistics, Probability and Uncertainty, 23 papers in Computational Mechanics and 11 papers in Artificial Intelligence. Recurrent topics in Cosmin Safta's work include Probabilistic and Robust Engineering Design (27 papers), Computational Fluid Dynamics and Aerodynamics (12 papers) and Combustion and flame dynamics (11 papers). Cosmin Safta is often cited by papers focused on Probabilistic and Robust Engineering Design (27 papers), Computational Fluid Dynamics and Aerodynamics (12 papers) and Combustion and flame dynamics (11 papers). Cosmin Safta collaborates with scholars based in United States, France and Germany. Cosmin Safta's co-authors include Habib N. Najm, Khachik Sargsyan, Bert Debusschere, Daniel Ricciuto, Cyrus K. Madnia, Peter Thornton, Jaideep Ray, Xun Huan, Guilhem Lacaze and Joseph Oefelein and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Journal of Computational Physics.

In The Last Decade

Cosmin Safta

72 papers receiving 795 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Cosmin Safta United States 16 278 266 158 125 90 75 829
M.‐D. Roselló Spain 14 209 0.8× 157 0.6× 128 0.8× 72 0.6× 42 0.5× 68 676
J.‐V. Romero Spain 14 232 0.8× 146 0.5× 128 0.8× 78 0.6× 42 0.5× 61 699
Marc Gerritsma Netherlands 18 560 2.0× 144 0.5× 85 0.5× 101 0.8× 72 0.8× 59 899
M. Pilch United States 10 728 2.6× 288 1.1× 101 0.6× 424 3.4× 80 0.9× 48 1.4k
Xingjian Wang United States 20 661 2.4× 90 0.3× 309 2.0× 188 1.5× 147 1.6× 68 1.1k
Jaideep Ray United States 17 384 1.4× 70 0.3× 67 0.4× 135 1.1× 18 0.2× 93 831
Maria Rightley United States 4 72 0.3× 264 1.0× 58 0.4× 65 0.5× 55 0.6× 8 640
Todd Oliver United States 16 771 2.8× 253 1.0× 66 0.4× 246 2.0× 25 0.3× 39 1.1k
Mohammad Khalil United States 15 131 0.5× 185 0.7× 62 0.4× 61 0.5× 97 1.1× 45 472
Axel Coussement Belgium 17 575 2.1× 48 0.2× 334 2.1× 232 1.9× 21 0.2× 62 906

Countries citing papers authored by Cosmin Safta

Since Specialization
Citations

This map shows the geographic impact of Cosmin Safta's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Cosmin Safta with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cosmin Safta more than expected).

Fields of papers citing papers by Cosmin Safta

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Cosmin Safta. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Cosmin Safta. The network helps show where Cosmin Safta may publish in the future.

Co-authorship network of co-authors of Cosmin Safta

This figure shows the co-authorship network connecting the top 25 collaborators of Cosmin Safta. A scholar is included among the top collaborators of Cosmin Safta based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Cosmin Safta. Cosmin Safta is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Asta, Mark, et al.. (2025). Accelerating phase field simulations through a hybrid adaptive Fourier neural operator with U-net backbone. eScholarship (California Digital Library). 11(1). 3 indexed citations
2.
Safta, Cosmin, et al.. (2025). Bayesian Calibration of Stochastic Agent Based Model via Random Forest. Statistics in Medicine. 44(6). e70029–e70029.
3.
Mihăescu, Lucian, et al.. (2025). Analysis of energy consumption for neutralization of the wastewater treatment plants sludge. E3S Web of Conferences. 608. 5017–5017. 1 indexed citations
4.
Fuhg, Jan N., et al.. (2024). Improving the performance of Stein variational inference through extreme sparsification of physically-constrained neural network models. Computer Methods in Applied Mechanics and Engineering. 432. 117359–117359. 4 indexed citations
5.
Patel, Ravi G., Cosmin Safta, & Reese E. Jones. (2024). Equivariant graph convolutional neural networks for the representation of homogenized anisotropic microstructural mechanical response. Computer Methods in Applied Mechanics and Engineering. 432. 117334–117334. 2 indexed citations
6.
Windl, Wolfgang, et al.. (2024). A BAYESIAN CALIBRATION FRAMEWORK WITH EMBEDDED MODEL ERROR FOR MODEL DIAGNOSTICS. International Journal for Uncertainty Quantification. 14(6). 37–70. 2 indexed citations
7.
Kim, Kyungjoo, et al.. (2023). CSPlib: A performance portable parallel software toolkit for analyzing complex kinetic mechanisms. Computer Physics Communications. 297. 109069–109069. 1 indexed citations
8.
9.
Safta, Cosmin, et al.. (2022). Trajectory design via unsupervised probabilistic learning on optimal manifolds. SHILAP Revista de lepidopterología. 3. 3 indexed citations
10.
Blonigan, Patrick, Jaideep Ray, & Cosmin Safta. (2021). Forecasting Multi-Wave Epidemics Through Bayesian Inference. Archives of Computational Methods in Engineering. 28(6). 4169–4183. 3 indexed citations
11.
Lee, Kookjin, Jaideep Ray, & Cosmin Safta. (2021). The predictive skill of convolutional neural networks models for disease forecasting. PLoS ONE. 16(7). e0254319–e0254319. 8 indexed citations
12.
Safta, Cosmin, et al.. (2021). MESH-BASED GRAPH CONVOLUTIONAL NEURAL NETWORKS FOR MODELING MATERIALS WITH MICROSTRUCTURE. 3(1). 1–30. 13 indexed citations
13.
Safta, Cosmin, Jaideep Ray, & Khachik Sargsyan. (2020). Characterization of partially observed epidemics through Bayesian inference: application to COVID-19. Computational Mechanics. 66(5). 1109–1129. 2 indexed citations
14.
Huan, Xun, Cosmin Safta, Khachik Sargsyan, et al.. (2019). Compressive sensing adaptation for polynomial chaos expansions. Journal of Computational Physics. 380. 29–47. 47 indexed citations
15.
Ghanem, Roger, Christian Soize, Cosmin Safta, et al.. (2019). Design optimization of a scramjet under uncertainty using probabilistic learning on manifolds. Journal of Computational Physics. 399. 108930–108930. 22 indexed citations
16.
Safta, Cosmin, et al.. (2019). Physics-informed Recurrent Neural Network Surrogates for E3SM Land Model. AGU Fall Meeting Abstracts. 2019. 2 indexed citations
17.
Mycek, Paul, Olivier Le Maı̂tre, Khachik Sargsyan, et al.. (2017). A resilient domain decomposition polynomial chaos solver for uncertain elliptic PDEs. Computer Physics Communications. 216. 18–34. 6 indexed citations
18.
Lu, Dan, Daniel Ricciuto, Anthony P. Walker, Cosmin Safta, & J. William Munger. (2017). Bayesian calibration of terrestrial ecosystem models: A study of advanced Markov chain Monte Carlo methods. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 3 indexed citations
19.
Lu, Dan, Daniel Ricciuto, Anthony P. Walker, Cosmin Safta, & J. William Munger. (2017). Bayesian calibration of terrestrial ecosystem models: a study of advanced Markov chain Monte Carlo methods. Biogeosciences. 14(18). 4295–4314. 34 indexed citations
20.
Safta, Cosmin, Daniel Ricciuto, Khachik Sargsyan, et al.. (2015). Global sensitivity analysis, probabilistic calibration, and predictive assessment for the data assimilation linked ecosystem carbon model. Geoscientific model development. 8(7). 1899–1918. 22 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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